Download The effects of US unconventional monetary policies in Latin America

THE EFFECTS OF US UNCONVENTIONAL
MONETARY POLICIES IN LATIN AMERICA
Fructuoso Borrallo, Ignacio Hernando
and Javier Vallés
Documentos de Trabajo
N.º 1606
2016
THE EFFECTS OF US UNCONVENTIONAL MONETARY POLICIES IN LATIN AMERICA
THE EFFECTS OF US UNCONVENTIONAL MONETARY POLICIES
IN LATIN AMERICA (*)
Fructuoso Borrallo, Ignacio Hernando and Javier Vallés
BANCO DE ESPAÑA
(*) We would like to thank Juan Londono, Henrique Basso, Luis Molina, Claudia Ramirez, Martin Suster and Adrian van
Rixtel, as well as participants at a Banco de España seminar, the November 2015 CEMLA workshop and the 13th
Emerging Markets Workshop (Oesterreichische Nationalbank). The views expressed in the paper are those of the
authors and do not necessarily reflect those of the Banco de España.
Documentos de Trabajo. N.º 1606
2016
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ISSN: 1579-8666 (on line)
Abstract
This paper offers an empirical analysis of the way in which US unconventional monetary
policy has affected Latin American countries. First, we estimate the effects of US monetary
policy announcements on sovereign bond interest rates, exchange rates and stock market
indices for a set of emerging countries, including five Latin American economies. We find that
QE announcements in 2008/2009 and the “tapering talk” in 2013 generated sizable
sovereign yield and exchange rate fluctuations. We further find some excess response of
Latam asset prices that disappear once we take into account their country characteristics. In
the second part of the paper we estimate a simple model that measures the influence of
country-specific macroeconomic fundamentals on the transmission of US financial
disturbances. An estimated model including the inflation rate, the CDS spread, the ratio of
official reserves and market capitalisation explains some of the observed cross-country
heterogeneity of spillovers from US monetary policy announcements. Under this model, a
greater impact from the normalisation of US monetary policy can be expected in Latin
America relative to other emerging economies.
Keywords: unconventional monetary policy, spillovers, emerging economies, event study.
JEL Classification: E52, F32, G11.
Resumen
Este trabajo ofrece un análisis empírico de la forma en que la política monetaria no convencional de
Estados Unidos ha afectado a los países de América Latina. En primer lugar, se estiman los
efectos de los anuncios de política monetaria de Estados Unidos sobre los tipos de interés de
los bonos soberanos, los tipos de cambio y los índices bursátiles para un conjunto de países
emergentes, incluyendo cinco economías de América Latina. Se encontró que los anuncios
de expansión cuantitativa (QE) en 2008/2009 y los relativos a la reducción del programa de
compras (tapering talk) en 2013 generaron grandes fluctuaciones de los rendimientos soberanos y
de los tipos de cambio. Se obtuvo alguna respuesta diferencial de los precios de los activos
en América Latina, que desaparece una vez se tienen en cuenta las características de los
países. En la segunda parte del documento se estima un modelo simple que mide la influencia
de los fundamentos macroeconómicos específicos de cada país en la transmisión de las
perturbaciones financieras de Estados Unidos. Un modelo estimado que incluye la tasa de
inflación, los diferenciales de los CDS soberanos, la proporción de reservas oficiales sobre PIB
y la capitalización del mercado bursátil explica parte de la heterogeneidad observada entre
países en los efectos de los anuncios de política monetaria de Estados Unidos. De acuerdo
con este modelo, cabe esperar un mayor impacto de la normalización de la política monetaria
de Estados Unidos sobre América Latina que sobre otras economías emergentes.
Palabras clave: política monetaria no convencional, transmisión internacional, economías
emergentes, estudio de eventos.
Códigos JEL: E52, F32, G11
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1
Introduction
After the 2007-2008 global financial crisis, once central banks in the major advanced economies had used up
conventional instruments, these central banks resorted to new, unconventional monetary policy tools to help
improve the weak economy. This unprecedented monetary policy reaction –and, perhaps more importantly,
the perception that major central banks were firmly committed to adopting any measure needed to preserve
an orderly financial intermediation– was instrumental in calming financial markets. Against this background,
from late 2009 until the beginning of the tapering tantrum in the spring of 2013, emerging market economies
(EME) received a high volume of capital flows that ran in parallel with asset appreciation and the reduction of
interest rates.
The opposite movement occurred after the Federal Reserve's announcement in May 2013 that
anticipated the end of expansionary monetary policy in the United States. There were sudden reversals of
capital inflows in several episodes between May 2013 and early 2014, as market perceptions of the Federal
Reserve’s intention to gradually withdraw its asset purchase programme firmed. Capital outflows from
emerging markets during these episodes led to exchange rate depreciations of emerging market currencies,
increases in the risk premia on their financial assets, and falls in their equity markets.
In this paper, we analyse the effects of US unconventional monetary policy announcements on
sovereign bond yields, exchange rates and stock market indices for twenty EMEs, including five from Latin
America, and we also explore how the transmission of such monetary impulses is influenced by countryspecific variables, such as macroeconomic variables, market conditions, and the external position, reflecting
the countries’ fundamentals. Thus, we analyse spillover effects by focusing on the reaction of the prices of
financial assets. But, admittedly, we disregard other dimensions of the international transmission of monetary
policy, namely changes in quantities (gross capital flows) and policy reactions.
This paper contributes to an already extensive literature which has explored the effects of the new
unconventional instruments, mainly asset purchase programmes in the United States. A number of papers have
focused on the impact of these programmes on the US economy. Although results differ across studies
depending on their methodology, sample periods, and variables analysed, a number of general conclusions can
be drawn. First, quantitative easing programmes have been successful in improving financial conditions,
sustaining activity and mitigating deflation risks (IMF, 2013). There is an ample literature that quantifies the effects
of balance sheet policies on asset pricing (Gagnon et al., 2011, Meaning and Zhu, 2011, Neely, 2010,
Krishnamurthy and Vissing-Jorgenson, 2011, among many others) and there is also some evidence, although
admittedly scarcer, documenting the fact that asset purchases provided significant stimulus to activity and
counteracted disinflationary pressures (Chen et al., 2012, for the US LSAP, and Kapetanios et al., 2012, or
Joyce et al., 2011, for the UK APF programs). Second, the effects of the subsequent programmes have been
documented as being progressively smaller (Krishnamurthy and Vissing-Jorgensen, 2011, and Bauer, 2012).
Third, three main transmission channels of unconventional monetary policy (UMP) measures are identified: the
portfolio-balance channel (increase in the demand for other riskier assets, reducing financing costs), the
signalling channel (reinforcement of the perception that the monetary policy stance will remain loose for a
prolonged period), and the confidence channel (increasing investors’ risk appetite) (Woodford, 2012, IMF, 2013).
With regards to the analysis of cross-border spillovers (especially to EMEs) of unconventional
monetary policy measures, the recent literature also offers some robust results. The overall picture provided
by this literature is that asset purchase programmes (especially those of the Federal Reserve) encouraged
capital flows to EMEs, leading to appreciations of their exchange rates, increases in their stock market indices
and contractions in their credit spreads. A number of papers have focused on more specific features.
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Fratzscher et al. (2013) document that LSAP1 policies induced a portfolio rebalancing from the rest of the
world into the US, in particular into US bonds lowering their yields. In contrast, LSAP2 policies triggered a
rebalancing from US funds into foreign funds, in particular EME equities. Bowman et al. (2014) found that the
effects of US unconventional monetary policy on EMEs’ financial assets prices depend on country-specific
time-varying characteristics. Comparing the impact of conventional and unconventional measures, Chen et al.
(2014) found that unconventional monetary policies had larger spillovers than conventional policies and they
argue that this result is explained by structural issues –related to the instruments used during the UMP
period– and, to a lesser extent, to weaker EME growth prospects. Gilchrist et al. (2014) also found a
substantial pass-through of unconventional US monetary policy to EME bond yields but with larger
heterogeneity than that observed in the transmission to advanced economies.
Finally, more recent papers have focused specifically on the cross-border impact of the “tapering
talk”. Market reaction to talk of tapering was initially indiscriminate during the bout of volatility in May-June
2013, although later some differential effects relating to fundamentals were observed (Sahay et al. 2014). In
particular, Eichengreen and Gupta (2013) and Aizenman et al. (2014) found that the impact was greater in
countries that had accumulated external vulnerabilities in terms of currency appreciation and a deteriorating
current account during the previous expansionary period, although liquidity, market depth, and the size of
investors’ holdings also influenced the magnitude of the spillover effects. Mishra et al. (2014), in keeping with
Bowman et al. (2014), showed that countries with stronger fundamentals, deeper financial markets, and a
tighter macroprudential policy stance in the run-up to the tapering announcements experienced smaller
currency depreciations and smaller increases in government bond yields. Sahay et al. (2014), reviewing the
evidence of the cross-border impact of the tapering period, conclude that those countries that responded
earlier and decisively to the initial tapering announcements fared better in later episodes of volatility in
international financial markets.
This paper adds to this literature in two respects. Its first contribution is to analyse whether the
impact of the US non-standard monetary policies on Latin American economies differs from the impact on
other EMEs. In this connection, there are reasons to expect that Latin American economies might be more
vulnerable to increases in US interest rates. First, although many Latin American economies have reduced
their reliance on dollar-denominated debt, this is still higher than in other EME economies. Second, financial
interdependencies with the United States are particularly high within this region. Third, the main export
products for most of these economies are commodities whose prices on international markets are set in US
dollars. All these factors support the large and significant responses of Latin American macroeconomic
variables to US monetary disturbances found in the literature in ‘normal times’ (Canova, 2005) and the higher
estimated sensitivity of sovereign bond yields in Latin America to US yields during the taper tantrum episode
(IMF, 2014). Nevertheless, if the normalisation of US monetary policy mirrors a better US growth performance,
for those economies that are close trading partners (e.g. Mexico) the positive impulse from stronger US
growth is likely to counteract the impact of the rise in US interest rates.
The second contribution of this paper is to explore whether the role of fundamentals in conditioning
the responses in EME economies to US unconventional monetary policy shocks differs across different
episodes. More precisely, country characteristics were more decisive in explaining differences in the reaction
to QE announcements than they were in response to news on the tapering process.
Taking together these two contributions, we want to test whether the impact of US non-standard
monetary policies on Latin American economies differs from the impact on other EMEs and, secondly,
whether or not these differences remain once we control for fundamentals.
The remainder of the paper is organised as follows. In section 2, using a daily panel data sample for
the period from October 2008 to April 2015, we first analyse the effects of US monetary policy
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announcements on sovereign bond yields, exchange rates, and stock market indices for 20 countries,
including five from Latin America. In section 3, we explore whether the reaction of EME asset prices to US
monetary policy differs depending on country-specific characteristics and whether the impact on Latin
American asset prices differs from that found for other EMEs. Section 4 summarizes the main results of the
paper and identifies some remaining issues.
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2
Event studies
This section presents an event study to show the effect of US policy changes on emerging markets. We
report the results for 2-day changes (from the day before to the day after) in foreign markets after monetary
policy announcements, assuming that economic news does not affect the policy choice in that short period of
time. The daily data run from October 1st, 2008 to April 24th, 2015. This is a simple alternative to VAR analysis
that considers the asset price changes in volatility (Wright, 2012) or in future interest rates (Gertler and Karadi,
2015) to identify the monetary shocks within the period of unconventional monetary policy. Thus, we refrain
from differentiating in the announcements between the impact effect and the signal about future policy
intentions (Chen et al. 2014), and we simply consider them as unanticipated events.
Our analysis covers three types of financial assets: 10-year sovereign bonds in local currency,
bilateral exchange rates relative to the US dollar, and headline stock market indices. Appendix I describes the
data sources and defines the variables and Appendix II presents a summary of statistics. The sample includes
the following 20 emerging economies: Brazil, Chile, China, Colombia, Czech Republic, Hong Kong, Hungary,
India, Indonesia, Korea, Malaysia, Mexico, Peru, Philippines, Poland, Singapore, South Africa, Taiwan,
Thailand, and Turkey. This country sample is similar to others considered recently in the literature but we will
also present some robustness analysis.
Table 1 describes the selected set of official announcements and speeches by the Federal Reserve
considered since the establishment of unconventional policies in November 2008. The set of events includes
announcements relating to the first two large-scale asset purchases (LSAP-1 and LSAP-2) in 2008-2009 and
in 2010, the maturity extension programme in 2011 (MEP), the third LSAP (LSAP-3) in 2012, the so-called
“tapering tantrum” in May-October 2013 and the official tapering period of asset purchases from December
2013 to October 2014. Besides these QE events we also consider statements on forward guidance policy
and some speeches by Chairman Bernanke that could prompt potential market reactions.
Figure 1 shows the time series for the aggregate index for EMEs, Latin American and US sovereign
yields (panel A) and stock market prices (panel B), along with the aggregate index for EMEs and Latin
American exchange rates with respect to the US dollar (panel C). This figure provides some insight into the
relationship between US unconventional monetary policy phases and EME financial asset prices. First, a comovement between US sovereign yields and EME (and Latin American) yields is observed, and it is clearer in
the case of the LSAP-1 and tapering periods. Second, the relationship between US unconventional monetary
policy measures and EME stock market prices and exchange rates is less clear. Third, the series of Latin
American financial asset prices display wider fluctuations than the corresponding aggregate EME series.
Figure 2 shows the time series for the aggregate capital inflows for different regions. In the aftermath
of the global financial crisis, capital flows displayed a steep upward trend in most emerging market regions
and particularly in Latin America, while the increase in advanced economies was less marked.
2.1
Emerging (and Latin American) market reactions
Tables 2, 3 and 4 report the 2-day changes in sovereign yields, exchange rates and stock prices, respectively,
around the 25 selected dates of the announcements.1 As a reference, in each table we include a first column
that reports the estimated changes in the US variable, a second column with the changes in the
corresponding aggregate EME index and a third column with the responses in a similar aggregate LATAM
1. The results for 1-day and 7-day windows around events do not differ much from those reported in the tables. And similarly when we
consider for Asian asset prices opening times in t+1.
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index. The fourth and fifth columns report the coefficients for a regression that considers as dependent
variables each of the assets not only with time variation but also with country variation:
∆
∑
∗
∑
∗ Lat ∗
[1]
where αi is a country fixed effect, βj is the coefficient associated with the dummy of each event (Dj) and γj refers
to the interaction coefficient of the event dummy with a Latam dummy (Lat). Thus, the coefficients reported in
column 4 (βj) represent the average change of the dependent variable at date j for a non-Latin American
country, while the sum of the coefficients reported in columns 4 and 5 (βj+γj) represent the average change of
the dependent variable at date j for a Latin American country.
US yields (first column in Table 2) dropped significantly around the first LSAP announcements,
except for the January 28th, 2009 event, at which time the yield rose. Fluctuations in US yields are smaller and
less significant around the second and third LSAP, and they are again significant around two of the MEP
announcements. Finally, the only significant reversal event with respect to yields is on June 19th, 2013, when
the FOMC suggested that tapering could begin in 2014. Other US assets such as the stock market index
(reported in Table 4) show more mixed results. The number of significant events is lower and in some cases a
fall is observed after the expansionary QE announcements.
Looking now at foreign assets, the changes in the EME aggregate yield index (GBI-EM in column 2,
Table 2) are less uniform and of a lower magnitude. As in the case of the United States, the most significant
events are those around the LSAP-1 and the tapering. The changes in EME exchange rates and the stock
market indices are relevant around the same dates although in general with a lower significance. The results
for the Latam aggregate yield index (column 3 in Table 2) are similar and, in general, of a larger size. The
different response of assets has already been reported by, among others, Bowman et al. (2014). More
generally, the decreasing effect of the different QE programmes has been documented in the US economy
(e.g. Krishnamurthy and Vissing-Jorgensen, 2011) and internationally (e.g. Fratzscher et al., 2013).
The last two columns in Table 2 allow us to see the significance of country variability and to test
whether the movements in sovereign yields around the relevant events differ in the Latin American countries
with respect to other emerging market economies. EME yields decreased on average 20 basis points within
the LSAP-1 period. We also find that after the first LSAP announcements the yields of the Latin American
countries fell more than did the whole sample of emerging economies, and that these differences were highly
significant for the December 2008 announcements2.
The decreasing effect of subsequent QE programmes in EME economies is clear since the
movements in yields are not significant between 2010 and 2012. The only exception is the August 2011
FOMC meeting, prior to the launching of the maturity extension programme (MEP) with a higher Latam effect
after Bernanke’s 2011 Jackson Hole speech. By contrast, when Operation Twist was launched in September
2011, the effect was the opposite, with a significant differential effect for Latin America. Finally, during the
tapering period, yield increases were found around the relevant dates of May and June 2013. The size of the
yield change was similar to the one during the LSAP-1 period and the reaction for Latin American countries
was significantly higher in June3.
A monetary shock that lowers US yields also generates an appreciation of the EME currencies (Table 3)
and an increase in the stock market indices of the EME economies (Table 4). Contrary to Fratzscher et al. (2013)
2. The p-value for the coefficient capturing the differential effect for Latin American economies to the FOMC statement in March 2009
extending the first LSAP was 0.14.
3. The p-value for the coefficient capturing the differential effect for Latin American economies to Bernanke’s testimony in May 2013 was 0.11.
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results, we do not find evidence of a significant US dollar appreciation during the LSAP1 period and that would
support a portfolio rebalancing out of EME assets into US assets.
Interestingly, the EME movements in exchange rates and stock markets are more significant when
the cross-country dimension of the data is taken into account than when looking to aggregate indices. And
we found more significant events for the EME coefficient with these two assets than with the yields. But again
the LSAP-1 and the Tapering periods are the most significant. For example the LSAP-1 caused, on average,
a dollar depreciation of 1%-2% and an increase of stock market of 2%.4 Nevertheless, other events did not
have the expected sign coefficient. In the case of exchange rate fluctuations, the depreciation after the June
2013 FOMC announcement of tapering was significantly greater in Latin America. This same pattern was also
observed around the March 2009 LSAP-1 announcement, but in this case Latam and aggregate EME moved
in opposite directions. The MEP announcement in September 2011 had a significant negative impact on
equity markets internationally and induced a cross-country rebalancing on bonds, especially out of Latam
yields and into US bonds that appreciated the dollar significantly, particularly against Latam currencies. After
the October 2014 FOMC meeting, when the tapering process concluded and an indefinite forward guidance
policy was announced, the aggregate Latam exchange rate against the US dollar appreciated. Thus, it seems
that Latam exchange rates were more sensitive to some of the US monetary shocks. On the contrary, there is
no evidence of a significant higher stock market response for the Latin American countries, with the exception
of the announcement on August 9th, 2011, when the FOMC assured that interest rates would remain
exceptionally low over the period to mid-2013.
In sum, a simple time series analysis of US unconventional monetary policies shows that they have
had a more significant effect across EME asset prices after the LSAP1 (2008-09) and the tapering (2013)
periods with some excess response by Latam assets. Comparing the three asset prices, the exchange rate is
the variable which has more significant events, consistently with the relevance of the exchange rate channel in
the transmission of monetary shocks to EME economies (Taylor, 2013).
4. When the regression analysis was repeated eliminating the five countries with higher per capita income the significant events and their
coefficients remain very much the same.
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3
Transmission of US monetary policy
This section examines the role played by country characteristics in financial market reactions to the Fed’s
policy actions. We first make use of the previous event study framework and analyse differences in
transmission between the previously identified positive and negative events. In the second part, we study
country heterogeneity in a monthly panel data set-up modeling a specific transmission channel. In both cases,
we test whether or not Latin American countries follow different patterns in response to the exogenous policy
announcements relative to the sample of emerging market economies (EMEs).
The country characteristics are detailed in Appendix I. They can be classified in four categories: i)
macro fundamentals: GDP growth, inflation, and public debt/GDP; ii) financial market conditions: CDS spread
and the policy interest rate; iii) external conditions: reserves/GDP, current account/GDP, external debt/GDP,
short-term external debt/GDP, net banking position/GDP, portfolio flows/GDP, nominal exchange rate
deviation, and the accumulated change in the real exchange rate; and iv) structural characteristics: an index of
financial openness; exports to the United States/GDP and stock market capitalisation (relative to GDP). Note
that among the external conditions, we have included two exchange rate indicators that measure the
competitiveness gains in the most recent period, and that among the structural variables we have included
stock market capitalisation as a proxy of financial market size.
Some of these characteristics may represent country vulnerabilities in the sense that the market
reaction of those country assets could be stronger in response to an exogenous shock. Others represent
country strengths and the market reaction to the US monetary policy announcement might be negatively
correlated with them. However, for variables that measure the level of financial and real integration as well as
the change in competitiveness, the effect may be more uncertain.
3.1
Market reaction and country characteristics: sample of UMP events
We initially estimate a set of regressions by pooling the previously identified 25 policy events across the 20
EMEs. The dependent variable Δyij is the 2-day change for one of three financial asset prices considered in
country i and event date j. The explanatory variables, besides the country fixed effect, include each of the
country characteristics (CCit-1), a dummy variable (
for the selected events that were significant (positively
or negatively) in the previous time-series regression, and the interaction between the significant event
dummies and the country characteristics. The specification is as follows:
∆
[2]
The regression with positive events includes three LSAP-1 dates that became significant across EME
or Latam economies in regression [1]: 11/25/08, 12/16/08, and 3/18/09. And the regression with the negative
events considers the two significant events during the tapering talk by the Fed: 5/22/13 and 6/19/13. All the
characteristics are lagged one month to avoid correlation with the error term.
Table 5 presents the regression results for changes in sovereign yields. For each of the country
characteristics, the left-hand side of the table reports the estimated coefficients for the regression with the
dummy variable under the significant LSAP-1 events and the interaction of the dummy with the
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characteristics. The right-hand side of the table reports the regression results under the significant tapering
events.5
First, the dummy variable for most of the country characteristics is significant and has a negative
effect for the LSAP-1 events (reducing yields) and a positive effect for the tapering events (increasing yields).
The exceptions are the dummy coefficients when including the inflation rate, the policy rate, and the CDS
since those characteristics are very much correlated with the countries’ bond yields. In general, the
significance around these events, their sign, and magnitude is consistent with the average event estimates in
Table 2.
A second result is that a number of the interaction coefficients are significant under the LSAP-1
whereas they are not so under the tapering events. Thus, we can say that on impact, the tapering had a more
indiscriminate effect across EMEs whereas the LSAP-1 had a differential effect across countries depending on
the country characteristics. During the LSAP-1 period countries with a higher inflation rate, higher CDS
spread, and higher policy rate yields responded more to the US monetary shock whereas countries with
higher current account surpluses or higher reserves yields responded less6. There is also a significant variable,
the external debt that does not affect yields with the expected sign when interacting with the LSAP-1 events.
Stock market capitalisation has a positive sign, indicating, in this case, that large markets reacted less to the
external shock, but it is not significant.
The results are even stronger when the dependent variable is the change in exchange rates (see
Table 6). In all the cases the dummy for the LSAP-1 event is significant, indicating the relevance of this
variable in the transmission of monetary policy shocks. There are three country characteristics that interact
significantly with the first set of unconventional Fed policies, which were also significant in the yields
regression: the domestic policy rate, the current account, and the reserves. Now the interaction with the
public debt instead of the inflation rate becomes significant and the external debt has the expected sign.
Moreover, two of the structural variables are significant: the market capitalization and the share of exports.
Again, most of the country characteristics are not significant when interacting with the tapering period.
These asset price responses around the first two months of the tapering process are consistent with
the indiscriminate impact of the earlier events, although market differentiation was gradually becoming more
relevant later on (Sahay et al., 2014). Nevertheless, these results differ from Mishra et al. (2014) since they find
that the impact of the taper talk was significantly related to macroeconomic fundamentals.
Next, we examine whether there are additional specific Latin American effects besides those
captured by the country characteristics. To that end, we repeat the estimation equation [2], adding an
interaction effect with a Latin American dummy (Lat) for each of the previous variables considered. The
specification is as follows:
∆
Lat
Lat
Lat
[3]
The estimation results for equation [3] with sovereign yields as the dependent variable and under the
relevant LSAP-1 events are presented in Table 7. As in the previous regression, we find a negative and
5. We do not report the general vulnerability coefficients since we are only interested in the effects around the significant policy events.
6. A one standard deviation increase in CDS (92,4 bp), the inflation rate (2,9%) and the policy rate (2,8%) implies an additional reduction in
sovereign yields after LSAP-1 announcements of 12 bp, 9 bp and 5 pb, respectively, while a one standard deviation increase in the reserves
to GDP ratio (28%) and the current account to GDP ratio (6,28) implies an increase in sovereign yields after LSAP-1 announcements of 11
bp, and 8 pb, respectively.
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significant dummy effect around those policy events. And their interactions with the country characteristics
remain significant and with the expected sign for the same variables: inflation, CDS spreads, policy rates,
reserves, the current account and the market capitalization. But the interaction of the LSAP-1 event and the
Lat dummy is not significant in most cases. And a similar result holds for the regression with the dummy for
the tapering talk events and the interaction with the Lat dummy.
We consider the above regression results as evidence of the rejection of an independent effect
coming out of the Latin American economies, once the country characteristics are taken into account to
explain the EME country heterogeneity when facing US monetary policy shocks. That spillover result qualifies
the excess response on Latam asset prices found in the event study section.
3.2
Channels of transmission
This section estimates a simple model for the transmission of unconventional US monetary policy. The
objective is to analyse whether the observed asset price responses for EME economies found in the event
study (section 2) correspond to the implied model response.
We adopt the specification of Bowman et al. (2014), which distinguishes the monetary policy effect
through US 10-year sovereign yields (ΔY
and high-yield corporate bond spreads (ΔY ):
∆
ΔY
∗ ΔY
∗ ΔY
[4]
Thus we characterise for the transmission of US monetary shocks through the interest rate channel
and the risk channel (ΔY ) that has been found for the US economy at the zero lower bound (e.g.
Rogers et al. 2013). The specification considers how international spillover differences may depend on the
country characteristics (
, consistent with the evidence presented in the previous section around policy
events. The specification [4] also includes a set of control variables ( ) to explain the changes in EME asset
prices: the VIX index, the change in commodity price index, and the change in the return on the S&P500
index. The model is estimated with monthly data for the period from October 2008 to December 2014.
The estimation results for yields, exchange rates, and the stock market index are reported in Tables
8, 9 and 10, respectively. We report the coefficients of the interactions of the country characteristics with the
changes in both US sovereign yields and high-yield corporate bonds (
and
) and their significant value.
In the panel regression of EME sovereign yields (Table 8), inflation is the only macroeconomic variable
with significant interactions. Countries with higher inflation are experiencing a higher response to fluctuations
in US sovereign yields and in high-yield bond spreads. But we do not find a similar result for the public debt
ratio or GDP growth. The market conditions measured by a high CDS spread or a high policy rate also
positively affect the response to US fluctuations since they may be proxies for financial risk. Four out of the
seven external variables considered are significant: the current account, reserves, portfolio flows, and the net
lending banking position all measure the strengthening of the external position of the country and
consequently reduce the variability of yields to US shocks. The external debt to GDP does not prove to be
significant7. Similarly, a positive nominal exchange rate deviation from its long-run baseline or the last year’s
cumulative real appreciation reflect vulnerability and cause larger changes in yields but they are not significant.
We also obtained that out of the three structural variables only market size is relevant. As in the
previous event regression, a bigger market size and thus a more liquid financial system reduces the response
7. Non-financial corporations’ external debt has raised after the global financial crisis in many EMEs. The interaction of that variable in
regression [4] was significant but with the sign opposed to the expected one.
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DOCUMENTO DE TRABAJO N.º 1606
of yields to a financial shock. This result is contrary to the more specific tapering evidence where investors
found it easier to rebalance their portfolios in larger EME economies and therefore experienced higher asset
price responses (Eichengreen and Gupta, 2013).
Table 9 presents the estimation results for the panel data model with the EME exchange rates. An
increase in the bilateral rate against the dollar represents a depreciation of the EME currency. Interestingly, a
similar group of country characteristics to the yields equation affect the exchange rate fluctuations in a
significant way. Higher inflation, higher policy rates, lower reserves, a lower current account, and a lower
market capitalization depreciate the exchange rate more after an increase in US sovereign yields or in highyield spreads. And Table 10 shows the estimation results for the EME stock market returns. The number of
significant country characteristics is smaller and the risk channel plays a more important role in this case.
We conducted some robustness exercises controlling for domestic variables besides global ones in
regression [4]. For example, when the Zit vector includes the countries’ policy rate, inflation rate, and output
growth, the same country characteristics became significant with the exception of the market size.
Moreover, once each of these characteristics is introduced into the panel regression, there is not a
significant common Latam dummy to explain any of the three asset price movements8. That reinforces the
previous specific event analysis (QE1 and tapering) where there was no evidence of excess sensitivity for Latin
American economies to US monetary disturbances once country-specific fundamentals are taken into
account.
Table 11 presents a joint estimation of the specific country variables for the EME sovereign yields.
Based on the R2 gains of the variable by variable estimation in Table 8, the multivariate specification considers
the following characteristics: CDS spread for market conditions, inflation for macroeconomic conditions, the
official reserves ratio for external conditions, and market capitalization for structural conditions. The three first
estimates are consistent with previous univariate estimations: an increase in CDS spread and inflation or a
decrease in reserves is related to a country’s higher vulnerability. By contrast, the coefficient of the stock
market capitalization is estimated with a positive sign, implying that relatively large markets display larger
responses to US monetary policy announcements9. When experimenting with an alternative set of relevant
country characteristics such as the current account or the policy rate, the results did not change much but
the explanatory power decreased.
This multivariate estimation is similar to one by Bowman et al. (2014) although they consider a
vulnerability index estimating a principal component of a set of macro variables and control for the currency
regime. Nevertheless, our estimates present two important differences: first, both channels of transmission,
sovereign yields and high-yield bond spreads, are relevant for explaining the heterogeneity of EME yields; and
second, the explanatory power of the country characteristics considered in our multivariate estimation is much
higher than their vulnerability index.
From the estimation results in Table 11 we can now compare the observed country response to US
monetary policy announcements with the implied response by the estimated model. Figure 3 shows the
average and one standard deviation of the model’s response to a change in US Treasury yields10. Thus,
taking the multivariate version of equation [4], we calculate the average response (
of the three
country characteristics for each of the countries for which we have data and their standard deviation from the
8. These results are not reported to save space.
9. The estimates of the joint specification for the two other asset prices (not reported) go in the same direction, although the coefficients
present a lower significance level.
10. An event study around the effect of US monetary policy announcements on the high-yield bond spread gave few significant events. That
is the reason to focus on the response through the Treasury yields.
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DOCUMENTO DE TRABAJO N.º 1606
parameters’ uncertainty. Similarly, Figure 3 draws the average country response (also relative to the US) using
the 2-day changes in the event study (table 2).
We find a large variability across countries. Nevertheless, for most of the countries in the sample the
responses to the US policy have not outsized the expected price response of the model once the parameter
uncertainty has been considered. The only country with an observed response above the upper limit of the
confidence band is Poland. Interestingly, the model for Brazil is in the limit. Brazil is an example of a large
EME with a relatively open capital account and a flexible exchange rate regime where carry trade operations
and thus capital flows have responded very significantly to external QE policies. Other Latin American
countries’ responses are within the model bands or have had a nil response, as seen in the case of Chile.
Thus, the observed EME heterogeneity of sovereign yields spillovers of unconventional US monetary policy,
including that of the Latam economies, can be explained to a large extent by the model setup above.
Finally, we used the estimated model [4] to obtain some inference relative to the future normalization
of US monetary policy. Figure 4 simulates a monetary shock that increases US sovereign bonds by 100 bp
vs. a shock that simultaneously increases sovereign bonds and high-yield spreads by 100 bp. We take the
estimated model as the true one and fix the parameter values abstracting any model uncertainty. The
simulation exercise considers the observed country characteristics on December 2014. There are two
significant results. First, the interest rate channel, represented by changes in the Treasury bond, is more
relevant than the risk channel represented by the high-yield spreads. The average EME yield response is 62
bp through the interest rate channel and 68 bp when adding the risk channel11. Second, the countries with
weaker economic fundamentals (Indonesia, Brazil or Turkey) respond more than the average country, and
thus experience a higher vulnerability to changes in US monetary conditions. Other group of countries
combines better fundamentals with lower sensitivity to US shocks like the Eastern European economies that
are more linked to the euro area (Poland, Hungary or Czech Republic). Moreover, the remaining Latin
American countries are above the EMEs average showing also a higher vulnerability. That is a consequence of
the relative deterioration of their financial and macroeconomic fundamentals at the end of the sample period
as a result of a number of shocks (slowdown of the Chinese economy, reduction of commodities’ prices, and
tightening of global financial conditions) that affected Latin American economies more severely.
11. A one standard deviation increase in CDS (92,4 bp), the inflation rate (2,9%) and the stock capitalization (258%) implies an increase in the
average EME yield response of 39 bp, 45 bp and 41 pb, respectively, while a one standard deviation increase in the reserves to GDP ratio
(28%) implies a 61 bp reduction in the average EME yield response.
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DOCUMENTO DE TRABAJO N.º 1606
4
Conclusions
The empirical literature has shown that Latin American economies are very sensitive to US monetary policy
shocks. Higher dollarization of assets and liabilities, closer financial and commercial links with the United
States, and dependency on the commodities cycle could account for this historically. Moreover, after the
financial crisis and the launching of unconventional monetary policies in advanced economies, Latin America
was one of the regions that received massive capital flows. Now that the US monetary cycle is starting to turn,
it is important to anticipate the asset price response considering country specificities, as this may be relevant
for designing the proper policy response.
First, we analyzed whether there was a significant impact of US non-standard monetary policies on
financial asset prices for a set of emerging economies, including five Latin American countries. The analysis of
policy events showed a more significant effect across EME asset prices after the first set of quantitative easing
announcements in 2008-09 and the tapering talk in 2013, consistent with previous results in the literature. We
also found an excess response by Latin American yields and exchange rates.
Second, we explored whether the role of fundamentals in conditioning the responses in EME
economies to US unconventional monetary policy shocks differed across different episodes. We found that a
set of country characteristics were relevant in explaining the first set of unconventional measures in 2008-09,
but that the tapering talk in 2013 initially had a more indiscriminate effect across EMEs. And in either case
there is no evidence of an independent effect coming out of the Latin American economies.
Finally, we estimated a simple model of the international transmission of US financial conditions that
incorporated the domestic country characteristics to explain the observed cross country differences. The
inflation rate, the CDS spread, the official reserves ratio, and the market capitalization are the most significant
variables for measuring the vulnerability of the EME economies, and Treasury yield changes are a relevant
channel to measure the spillover effects of US financial shocks. On average, the observed event responses to
US unconventional monetary policies were within the estimated model bands, including those of the five Latin
American countries in our sample.
Overall, we showed that the intensity of the reaction of a number of financial asset prices in emerging
economies to US monetary policy announcements depends on macroeconomic fundamentals. In particular,
we found that a parsimonious model including CDS spreads, the ratio of official reserves to GDP, the inflation
rate, and the market capitalization explains, to a large extent, the cross-country heterogeneity in the spillovers
of US monetary policy. In addition, although we found some excess response of Latin American asset prices
to recent US monetary policy announcements, this differential response disappears once we take into
account country-specific characteristics. In light of our results, the current deterioration of macroeconomic
fundamentals in the Latin American region suggests that they are particularly vulnerable to the foreseeable
normalization of the US monetary policy.
The evidence provided by the effect of US monetary policies on EME asset prices did not consider
the policy responses and the exchange rate framework of the domestic economies. These are relevant
aspects to be considered in future work. Moreover, this future work should also consider the response of
other financial market variables (dollar-denominated sovereign bonds, corporate bonds, capital flows, to name
a few) to US monetary policy measures, in order to assess the robustness of our spillover results.
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DOCUMENTO DE TRABAJO N.º 1606
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Appendix I. Definitions of the variables
DEPENDENT VARIABLES
DESCRIPTION
SOURCE
SOVEREIGN YIELDS
IN LOCAL CURRENCY
BLOOMBERG*
EXCHANGE RATES
BILATERAL EXCHANGE RATE WITH US DOLLAR
DATASTREAM
-
STOCK MARKET PRICES
AGGREGATE INDEX
REUTERS
‐
UNAVAILABILITY
-
COUNTRY CHARACTERISTICS
DESCRIPTION
SOURCE
GDP
YEAR TO YEAR GDP GROWTH.
NATIONAL STATISTICS, IFS, OECD
UNAVAILABILITY
INFLATION
YEAR TO YEAR CONSUMER PRICE INDEX GROWTH
NATIONAL STATISTICS, IFS
-
DEBT TO GDP
PUBLIC DEBT TO GDP (%)
OXFORD ECONOMICS
CHILE
-
POLICY RATE
OFFICIAL INTEREST RATE, SET BY THE CENTRAL BANK
NATIONAL CENTRAL BANKS, IFS
CHINA, SINGAPORE, TAIWAN
CDS
CREDIT DEFAULT SPREAD
DATASTREAM
SOUTH AFRICA, SINGAPORE, TAIWAN, INDIA
CURRENT ACCOUNT
CURRENT ACCOUNT BALANCE RESPECT TO GDP (%). (+): SURPLUS, (-): DEFICIT
NATIONAL STATISTICS, IFS, OECD, OXFORD ECONOMICS-
RESERVES
RESERVES ASSETS TO GDP (%)
NATIONAL STATISTIS, DATASTREAM, IFS
-
EXTERNAL DEBT
EXTERNAL DEBT TO GDP (%)
NATIONAL STATISTICS, OXFORD ECONOMICS
SINGAPORE, MALAYSIA, PHILIPPINES, HONG KONG, TAIWAN, KOREA
PORTFOLIO FLOW
NET INFLOWS OF CAPITAL TO GDP (%)
NATIONAL STATISTICS, IFS, OECD, DATASTREAM
SINGAPORE, MALAYSIA, PHILIPPINES, HONG KONG, TAIWAN
NET BANKING POSITION
FOREIGN ASSETS MINUS FOREIGN LIABILITIES TO GDP (%)
NATIONAL STATISTICS, IFS
SINGAPORE, MALAYSIA, PHILIPPINES, HONG KONG, TAIWAN, POLAND,
EXCHANGE RATE DEVIATION
DEVIATION FROM EQUILIBRIUM EXCHANGE RATE (PROXIED AS A DEVIATION FROM THE HISTORICAL AVERAGE).
JP MORGAN
SINGAPORE, MALAYSIA, PHILIPPINES, HONG KONG, TAIWAN
REAL EXCHANGE RATE GROWTH
LAST YEAR REAL EXCHANGE RATE GROWTH. AN INCREASE IS AN APPRECIATION
JP MORGAN
-
KOREA
A POSITIVE VALUE INDICATES THAT THE NATIONAL CURRENCY IS OVERPRICED
OF THE NATIONAL CURRENCY.
CAPITALISATION
STOCK MARKET CAPITALISATION TO GDP
BLOOMBERG
-
CHINN ITO INDEX
CHINN AND ITO INDEX. AN INCREASE IN THE VALUE IMPLIES A GREATER
CHINN AND ITO WEB
TAIWAN
NATIONAL STATISTICS, FRED
-
DEGREE OF OPENNESS OF THE FINANCIAL ACCOUNT
EXPORTS
US EXPORTS TO GDP (%)
* FOR CHILE, THE SOURCE IS CENTRAL BANK OF CHILE AND FOR BRAZIL, THE SOURCE IS DE POOTER ET AL (2013)
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DOCUMENTO DE TRABAJO N.º 1606
Appendix II. Summary statistics
VARIABLE
OBS
MEAN
STANDARD DEVIATION
MIN
YIELDS (ONE MONTH CHANGE)
1500
-0.04
0.50
-4.39
MAX
4.30
EXCHANGE RATES (ONE MONTH CHANGE)
1500
0.12
4.42
-14.02
26.69
STOCK INDICES (ONE MONTH CHANGE)
1500
0.77
6.39
-37.28
38.46
GDP GROWTH
1500
3.61
3.86
-14.74
18.86
INFLATION
1500
3.67
2.94
-9.48
16.22
CURRENT ACCOUNT TO GDP
1500
1.36
6.28
-9.55
24.18
CHINN ITO INDEX
969
0.53
1.39
-1.18
2.42
EXPORTS TO GDP
1500
4.73
4.69
0.42
25.67
CDS
1200
178.97
92.36
51.00
725.00
POLICY RATE
1275
4.41
2.76
0.05
16.75
CAPITALISATION
1500
1.35
2.58
0.99
14.94
DEBT TO GDP
1500
44.11
22.00
3.79
106.65
NET BANKING POSITION
1022
-0.33
21.25
-27.66
90.39
EXTERNAL DEBT
1035
37.12
30.20
3.31
148.15
PORTFOLIO FLOW
1023
2.19
3.27
-6.46
16.85
EXCHANGE RATE DEVIATION
1080
7.78
18.86
-35.70
72.74
RESERVES
1500
33.32
27.70
8.78
122.13
REAL EXCHANGE RATE GROWTH
1500
-0.39
7.14
-30.00
30.90
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TABLE 1. LIST OF RELEVANT FOMC MEETINGS AND EVENTS: NOVEMBER, 2008- OCTOBER, 2014
FIRST LARGE SCALE ASSET PURCHASE (LSAP)
11/25/2008
Announcement
The Fed announces the purchases of MBS backed by government agencies, and the creation of TALF
12/01/2008
Speech (Austin)
Bernanke hints future Treasury purchases
12/16/2008
FOMC statement
The Fed cuts the target Federal Funds rate to zero
01/28/2009
FOMC statement
The Fed announces the PDCF, the TLSF and the AMFL
03/18/2009
FOMC statement
The Fed extends its purchases of MBS and announces that will start to purchase Treasury securities
SECOND LSAP
08/10/2010
FOMC statement
The Fed announces his willing to buy long-term Treasury securities through reinvestment of payments of its
MBS
08/27/2010
Speech (Jackson Hole)
Bernanke's speech at Jackson Hole
09/21/2010
10/15/2010
FOMC statement
Speech (Indiana)
According to the FOMC, the short term interest rate will stay at low levels for a long period of time
According to Chairman Bernanke, new measures might be necessary
11/02/2010
FOMC statement
The Fed decides to purchase additional 600 billions of dollars of long-term Treasury securities
MATURITY EXTENSION PROGRAM (MEP)
According to the FOMC, the short term interest rate will stay at low levels for a long period of time and will
take new measures if neccessary
08/09/2011
FOMC statement
08/26/2011
Speech
Bernanke's speech at Jackson Hole
09/21/2011
FOMC statement
The Fed announces its Maturity Expansion Program
08/22/2012
08/31/2012
FOMC minutes
Speech (Jackson Hole)
The Fed will take new measures if neccesary
Chairman Bernanke suggests new QE
09/13/2012
FOMC statement
The Fed announces new Quantitative Easing
THIRD LSAP
EVENTS IN 2013
03/20/2013
FOMC statement
The Fed will continue its accomodative monetarty policy until certain goals of unemployment and inflation are
reached
05/01/2013
FOMC statement
FOMC: accomodative monetary policy will be held for a long period of time
TAPER TALK PERIOD
05/22/2013
FOMC minutes and testimony
Bernanke suggests the end of expansive monetary policy
06/19/2013
FOMC statement
The Fed suggests that "tapering" could begin nex year
07/11/2013
FOMC minutes and
speech (NBER)
Bernanke says that the central bank's easing monetary policy would stay for the foreseeable future
10/30/2013
FOMC statement
The Fed decides to continue its accomodative monetary policy
12/18/2013
FOMC statement
"Tapering" is oficially announced
EVENTS IN 2014
09/17/2014
FOMC statement
Announce of policy normalization principles and plans
10/29/2014
FOMC statement
Concluded tapering period. Starts "indefinite" forward guidance
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TABLE 2. EVENT STUDY FOR CHANGES IN SOVEREIGN YIELDS: DAILY DATA (30/09/2008-24/04/2015)
Dates
US yields
EME GBI index
Latam GBI index
∆
∗
∗ Lat ∗
Event effect (
Latam effect (
First LSAP
11/25/2008
-33.84***
-21.46***
-22.24**
-15.56***
2.26
12/1/2008
-26.46***
-2.86
-25.04**
-2.25
-50.51***
12/16/2008
-33.23***
-16.86**
-12.74
-29.36***
1.95
1/28/2009
29.88***
9.24
10.46
4.11
-6.94
3/18/2009
-40.31***
-5.86
9.84
-7.63**
-10.34
8/10/2010
-14.59*
-2.96
-6.84
-2.64
-4.16
8/27/2010
5.28
4.14
7.36
2.44
4.62
9/21/2010
-14.25*
-3.26
-2.84
-1.09
-3.42
10/15/2010
0.64
1.34
3.66
4.36
-6.61
11/3/2010
-12.58
-2.06
0.00
0.93
0.12
8/9/2011
-19.87**
-8.06
-13.14
-6.74*
3.33
8/26/2011
5.33
-5.56
-10.44
1.48
-11.45*
9/21/2011
-22.57***
17.24**
21.36**
4.65
20.57***
8/22/2012
-13.87*
-7.36
-11.94
-2.94
-1.00
8/31/2012
-6.47
-3.87
-1.94
-3.09
2.87
9/13/2012
10.63
4.04
4.36
2.15
6.14
3/20/2013
2.19
2.01
3.06
0.94
3.19
5/1/2013
-4.49
-3.89
-1.84
-4.02
1.41
5/22/2013
8.03
9.84
12.86
6.27*
11.12
6/19/2013
23.84***
36.64***
46.76***
23.80***
14.35**
7/11/2013
-7.56
-5.26
-9.54
-2.56
-3.83
10/30/2013
3.76
18.04**
35.06***
5.34
3.79
12/18/2013
8.37
1.84
-0.24
3.58
2.91
9/17/2014
4.15
1.54
0.02
0.11
1.56
10/29/2014
2.44
5.24
0.12
0.84
-1.18
Second LSAP
MEP
Third LSAP
Events in 2013
Events in 2014
Note: Column 2 reports the changes in U.S. 10-year sovereign yields. Columns 3 and 4 report the changes in
two aggregate indexes. Columns 5 and 6 report the average country changes and their significance level. *, **
and *** represent significance at the standard 10, 5 and 1 percent confidence level.
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 3: EVENT STUDY FOR CHANGES IN EXCHANGE RATES (DEPRECIATION RATES):
DAILY DATA ( 30/09/2008-24/04/2015)
Dates
EME index
Latam index
∆
∗
∗ Lat ∗
Event effect (
Latam effect (
-1.22***
0.11
1.07***
-0.31
First LSAP
11/25/2008
-0.76*
-1.46
12/1/2008
0.89**
0.81
12/16/2008
-0.96**
-1.11
-1.68***
0.03
1/28/2009
0.05
-0.69
0.38
-0.27
3/18/2009
-0.74*
-0.39
-1.48***
1.69***
8/10/2010
0.55
0.56
0.94***
-0.75
8/27/2010
0.01
0.07
-0.06
-0.18
9/21/2010
-0.36
-0.44
-0.78***
0.66
10/15/2010
0.19
0.07
0.64**
-0.38
11/3/2010
-0.62
-0.99
-0.91***
0.41
8/9/2011
0.19
0.42
0.22
0.53
8/26/2011
-0.35
-0.55
-0.44
0.17
9/21/2011
1.67***
5.12***
1.74***
1.80***
8/22/2012
-0.19
0.17
-0.32
0.19
8/31/2012
-0.33
-0.95
-0.29
-0.28
9/13/2012
-0.62
-1.00
-0.79***
0.16
3/20/2013
0.08
0.11
0.14
-0.13
5/1/2013
-0.21
0.27
-0.18
0.28
5/22/2013
0.51
0.66
0.36
0.31
6/19/2013
1.46***
3.43***
1.44***
1.01*
7/11/2013
-0.34
-0.42
-0.69**
0.27
10/30/2013
0.32
0.83
0.41
0.15
12/18/2013
0.51
0.82
0.57**
-0.05
9/17/2014
0.27
0.65
0.35
-0.25
10/29/2014
-0.02
-1.80*
0.23
-1.37**
Second LSAP
MEP
Third LSAP
Events in 2013
Events in 2014
Note: Columns 2 and 3 report the changes in two aggregate indices. Columns 3 and 4 report the average
country changes and their significance level. *, ** and *** represent significance at the standard 10, 5 and
1 percent confidence levels.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 4: EVENT STUDY FOR CHANGES IN STOCK MARKET INDEX: DAILY DATA
( 30/09/2008-24/04/2015)
Dates
US S&P 500
MSCI EME index
MSCI Latam. index
∆
∗
∗ Lat ∗
Event effect (
Latam effect (
First LSAP
11/25/2008
4.12**
5.66***
6.23**
3.33***
-0.87
12/1/2008
-5.38***
-4.94**
-7.99***
-3.48***
0.32
12/16/2008
4.04**
4.12*
6.25**
1.36**
1.32
1/28/2009
-0.15
2.50
2.49
1.28**
-0.41
3/18/2009
0.67
2.81
3.10
2.10***
0.27
8/10/2010
-3.49*
-3.38
-3.80
-2.00***
-0.10
8/27/2010
0.08
0.59
0.66
0.59
0.24
9/21/2010
-0.82
0.31
-0.22
0.14
0.14
10/15/2010
0.84
-1.37
-0.18
-0.58
-0.27
11/3/2010
2.22
2.34
3.07
1.49***
-0.04
8/9/2011
0.03
-1.01
3.79
-2.45***
6.09***
8/26/2011
4.30**
3.19
4.12
1.26**
1.44
9/21/2011
-6.12***
-7.47***
-9.57***
-4.12***
-1.38
8/22/2012
-0.87
-0.20
-0.80
-0.17
-0.36
8/31/2012
0.42
0.84
0.92
0.87*
-0.88
9/13/2012
1.95
3.58*
3.58
1.76***
0.55
3/20/2013
-0.25
-0.30
-0.22
-0.09
0.20
5/1/2013
-0.09
-0.26
-1.07
0.14
-0.27
5/22/2013
-1.20
-2.17
-1.43
-1.18**
1.08
6/19/2013
-3.94**
-4.78**
-6.57**
-3.34***
-0.43
7/11/2013
1.58
3.19
1.84
2.57***
-1.29
10/30/2013
-0.96
-0.28
-1.05
-0.28
-0.13
12/18/2013
1.52
-0.04
0.72
-0.08
0.49
9/17/2014
0.53
0.16
-1.16
0.70
-0.70
10/29/2014
0.40
1.46
2.27
0.88*
-0.47
Second LSAP
MEP
Third LSAP
Events in 2013
Events in 2014
Note: Column 2 reports the changes in the S&P 500 returns. Columns 2 and 3 report the changes in two
aggregate return indexes. Columns 4 and 5 report the average country change and their significance level. *, **
and *** represent significance at the standard 10, 5 and 1 percent confidence levels.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 5: EFFECT OF THE LSAP-1 AND THE TAPERING TALK PERIODS ON EMERGING MARKET
YIELDS AND THEIR RELATIONSHIP TO COUNTRY CHARACTERISTICS
∆
LASP1 PERIOD
DUMMY (β) DUMMY*CC (δ)
Macroeconomic variables
GDP
Inflation
Debt
TAPERING TALK PERIOD
DUMMY (β) DUMMY*CC (δ)
-0.181***
0.063
-0.236***
-0.006
-0.042***
0.001
0.234***
0.120**
0.262***
-0.007
0.019
-0.001
-0.030
0.112
-0.018**
-0.001***
0.199***
0.104
-0.001
0.000
External variables
Current account to GDP
Reserves to GDP
External debt to GDP
Portfolio flows to GDP
Net banking position to GDP
Exchange rate deviation
Real exchange rate
-0.209***
-0.314***
-0.303***
-0.217***
-0.208***
-0.196***
-0.188***
0.012***
0.004***
0.003*
-0.001
0.002
0.000
-0.001
0.203***
0.266***
0.234***
0.222***
0.210***
0.202***
0.196***
-0.012**
-0.002
-0.000
0.004
-0.005**
0.001
0.003
Structural variables
Market size (capitalisation to GDP)
Real integration (exports to US to GDP)
Financial integration (Chinn Ito index)
-0.215***
-0.223***
-0.187***
0.032
0.004
0.025
0.220***
0.189***
0.000
0.003
Market conditions
Policy rate
CDS
Notes: This table reports the set of regressions pooling the 25 policy events across the 20 EMEs. Each line contains
the regression results for one of the country characteristics (CC) and the corresponding event period. In the LSAP1
period the dates considered are 11/25/08; 12/16/08 and 18/03/09. In the tapering talk period the dates are 22/5/13
and 19/6/2013. The general country characteristics coefficients are not reported. *, ** and *** represent significance at
the standard 10, 5 and 1 percent confidence levels.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 6. EFFECT OF THE LSAP-1 AND THE TAPERING TALK PERIOD ON EMERGING MARKET
EXCHANGE RATES AND THEIR RELATIONSHIP TO COUNTRY CHARACTERISTICS
∆
LSAP1 PERIOD
DUMMY (β) DUMMY*CC (δ)
TAPERING TALK PERIOD
DUMMY (β) DUMMY*CC(δ)
Macroeconomic variables
GDP
Inflation
Debt
-1.686***
-1.366***
-0.851**
0.043
-0.032
-0.0153*
1.716***
0.854**
0.557
-0.172**
0.064
0.011
Market conditions
Policy rate
CDS
-0.920**
-1.481***
-0.121**
-0.001
0.814
0.358
0.092
0.005
External variables
Current account to GDP
Reserves to GDP
External debt to GDP
Portfolio flows to GDP
Net banking position to GDP
Exchange rate deviation
Real exchange rate
-1.633***
-2.042***
-0.705**
-1.849***
-1.704***
-1.433***
-1.871***
0.076***
0.017**
-0.036***
0.038
-0.014
0.015
0.007
1.158***
1.575***
0.745
1.170***
1.284***
1.042***
1.326***
-0.043
-0.013*
0.013
0.055
-0.003
0.025
0.006
0.243*
0.076**
-0.154
1.305***
0.992***
-0.136*
0.024
Structural variables
Market size (capitalisation to GDP)
-1.723***
Real integration (exports to US to GDP) -2.058***
Financial integration (Chinn Ito index)
-1.426***
Notes: This table reports the set of regressions pooling the 25 policy events across the 20 EMEs. Each line contains
the regression results for one of the country characteristics (CC) and the corresponding event period. In the LSAP1
period the dates considered are 11/25/08; 12/16/08 and 18/03/09. In the tapering talk period the dates are 22/5/13
and 19/6/2013. The general country characteristics coefficients are not reported. *, ** and *** represent significance
at the standard 10, 5 and 1 percent confidence levels.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 7. EFFECT OF THE LSAP-1 ON EMERGING AND LATIN AMERICAN ECONOMIES YIELDS DEPENDING
ON THEIR COUNTRY CHARACTERISTICS
∆
Lat
DUMMY (β)
Lat
Lat
DUMMY*CC (δ)
DUMMY*LAT (η)
DUMMY*LAT*CC (ρ)
-0.167***
0.076
-0.300***
-0.010
-0.048***
0.001
-0.079
-0.329
0.246**
0.024
0.067**
-0.005*
-0.016
0.139*
-0.029***
-0.001***
-0.027
-0.313
0.025
0.002**
External variables
Current account to GDP
Reserves to GDP
External debt to GDP
Portfolio flows to GDP
Net banking position to GDP
Exchange rate deviation
Real exchange rate
-0.230***
0.360***
-0.338***
-0.233***
-0.235***
-0.249***
-0.190***
0.013***
0.004***
0.002
-0.003
0.002
0.001
0.001
0.029
0.026
0.041
0.017
-0.001
0.184***
0.010
-0.011
0.005
0.003
0.021
-0.009
-0.002
-0.003
Structural variables
Market size (capitalisation to GDP)
Real integration (exports to US to GDP)
Financial integration (Chinn Ito index)
-0.222***
-0.281***
-0.201***
0.026
0.021**
0.0186
-0.114
0.109
-0.002
0.518*
-0.024**
0.05
Macroeconomic variables
GDP
Inflation
Debt
Market conditions
Policy rate
CDS
Notes: This table reports the set of regressions pooling the 25 policy events across the 20 EMEs. Each line contains the regression results for one of the country
characteristics (CC) and the corresponding event period. In the LSAP1 period the dates considered are 11/25/08; 12/16/08 and 18/03/09. The general country
characteristics coefficients are not reported. *, ** and *** represent significance at the standard 10, 5 and 1 percent confidence levels.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 8. REACTION OF EMERGING MARKET YIELDS
TO US FINANCIAL VARIABLES
∆
Country
Variables
Macroeconomic variables
GDP
Inflation
∗ ΔY
∗ ΔY
U. S. Sovereign
yield (β2 )
U. S. High Yield
Spread (γ2 )
R2 gains
0.000
0.137***
0.001
0.026**
0.01
6.16
0.002
0.001
0.26
Policy rate
0.176***
0.040***
10.96
CDS
0.005***
0.001***
10.40
-0.043***
-0.011***
-0.001
-0.014***
-0.004***
0.001
3.63
4.42
0.39
-0.057**
-0.010**
0.010
-0.000
-0.029
-0.016***
-0.004***
0.003
0.004
-0.017***
1.56
2.33
0.99
0.49
-0.051*
-0.033
-0.003
-0.031***
-0.009
0.001
1.59
0.88
0.00
Debt to GDP
Market conditions
External variables
Current account to GDP
Reserves to GDP
External debt to GDP
Portfolio flows to GDP
Net banking position to GDP
Exchange rate deviation
Real exchange rate increase
Outstanding international debt
Structural variables
Market size (capitalization to GDP)
Real integration (exports to US to GDP)
Financial integration (Chinn e Ito index)
Note: ∆y is the one-month change in each EME sovereign bond yield. *, ** and *** represent significance at the standard 10, 5 and 1
percent confidence levels where standard deviations are corrected by panel-data Newey West.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 9 REACTION OF EMERGING MARKET EXCHANGE RATES
TO US FINANCIAL VARIABLES
∆
Country
Variables
Macroeconomic variables
GDP
Inflation
Debt to GDP
∗ ΔY
∗ ΔY
U. S. Sovereign
yield (β2 )
U. S. High Yield
Spread (γ2 )
R2 gains
-0.058
0.314***
-0.028
0.130***
0.09
1.67
-0.008
0.008
0.39
0.260
0.127***
1.51
0.008**
0.004***
2.00
-0.154***
-0.044***
0.027
-0.096***
-0.029***
0.016**
3.25
4.06
1.36
-0.200**
-0.025
-0.010
-0.037
-0.185***
-0.047
-0.0125***
0.002
-0.021
-0.106***
0.33
0.30
0.03
0.25
-0.333***
-0.123
0.244
-0.240***
-0.052
-0.035
1.39
0.50
0.13
Market conditions
Policy rate
CDS
External variables
Current account to GDP
Reserves to GDP
External debt to GDP
Portfolio flows to GDP
Net banking position to GDP
Exchange rate deviation
Real exchange rate increase
Outstanding international debt
Structural variables
Market size (capitalization to GDP)
Real integration (exports to US to GDP)
Financial integration (Chinn e Ito index)
Note: ∆y is the one-month depreciation rate of each EME currency with respect to the US dollar. *, ** and *** represent significance at
the standard 10, 5 and 1 percent confidence levels where standard deviations are corrected by panel-data Newey West.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 10. REACTION OF EMERGING MARKET STOCK INDICES
∆
Country
Variables
Macroeconomic variables
GDP
Inflation
∗ ΔY
∗ ΔY
U. S. Sovereign
yield (β2 )
U. S. High Yield
Spread (γ2 )
R2 gains
-0.311**
-0.304**
0.036
-0.049
0.49
0.16
0.005
-0.017**
0.44
Policy rate
-0.098
-0.021
0.02
CDS
-0.006
-0.001
0.07
0.092
0.025
-0.005
0.013
-0.003
-0.022***
0.05
0.14
2.51
0.193
0.003
-0.013
-0.055
0.047
-0.007
-0.005
-0.002
-0.005
-0.002
1.9
0.14
0.89
0.03
0.000
0.079
-0.412
-0.000
0.0960***
-0.319**
0.02
0.54
0.01
Debt to GDP
Market conditions
External variables
Current account to GDP
Reserves to GDP
External debt to GDP
Portfolio flows to GDP
Net banking position to GDP
Exchange rate deviation
Real exchange rate increase
Outstanding international debt
Structural variables
Market size (capitalization to GDP)
Real integration (exports to US to GDP)
Financial integration (Chinn e Ito index)
Note: ∆y is the one-month return of each EME country stock market index. *, ** and *** represent significance at the standard
10, 5 and 1 percent confidence levels where standard deviations are corrected by panel-data Newey West
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
TABLE 11. MULTIVARIATE ANALYSIS OF THE REACTION OF EMERGING MARKET YIELDS
TO US FINANCIAL VARIABLES
∆
∗ ΔY
(1)
Inflation
US sovereign yield
High yield spread
2
R gains
CDS
US sovereign yield
High yield spread
2
R gains
Reserves
US sovereign yield
High yield spread
2
R gains
Capitalisation to GDP
US sovereign yield
High yield spread
2
R gains
0.201***
0.039***
10.38
∗ ΔY
SPECIFICATIONS
(2)
(3)
(4)
0.151***
0.019**
0.144***
0.014
0.115**
0.009
0.003***
0.001***
0.003**
0.001***
0.003***
0.001***
‐0.003
‐0.003**
‐0.017**
‐0.005**
13.55
14.30
0.134***
0.026
15.04
Note: ∆y is the one-month change in each EME sovereign bond yield. *, ** and *** represent significance
at the standard 10, 5 and 1 percent confidence levels where standard deviations are corrected by paneldata Newey West.
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
FIGURE 1. EMERGING MARKET ASSET PRICES AND US FINANCIAL VARIABLES
12
GBI
%
QE1
MEP
QE2
QE3
TAPERING
2014
10
8
6
4
2
0
01/10/2008
01/10/2009
01/10/2010
01/10/2011
UNITED STATES
01/10/2012
LATINAMERICA GBI
01/10/2013
01/10/2014
EMERGING MARKETS GBI
SOURCE: JPMORGAN, FEDERAL RESERVE
160
EXCHANGE RATES
30/9/2008=100
QE2
QE1
MEP
QE3
TAPERING
2014
150
140
130
120
110
100
90
01/10/2008
01/10/2009
01/10/2010
01/10/2011
LATINAMERICA EXCHANGE RATE
01/10/2012
01/10/2013
01/10/2014
EMERGING MARKETS EXCHANGE RATE
SOURCE: NATIONAL SOURCES AND OWN CALCULATIONS
190
STOCK MARKET INDICES
30/9/2008=100
QE1
QE2
MEP
QE3
TAPERING
2014
170
150
130
110
90
70
50
01/10/2008
01/10/2009
01/10/2010
STANDARD AND POORS
01/10/2011
SOURCE: STANDARD AND POORS, MORGAN STANLEY
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
01/10/2012
LATINAMERICA MSCI
01/10/2013
EMERGING MARKETS MSCI
01/10/2014
FIGURE 2. CAPITAL INFLOWS: CHANGING DISTRIBUTION 2004-2013
UNIT: BILLIONS OF US DOLLARS
CAPITAL INFLOWS IN EMERGING ECONOMIES
US $ billions
25000
20000
15000
10000
5000
0
-5000
2006
2007
Middle East
SOURCE: IFS
BANCO DE ESPAÑA
34
DOCUMENTO DE TRABAJO N.º 1606
2008
2009
Europe
2010
2011
Asia
2012
2013
Latam
FIGURE 3. AVERAGE RESPONSE OF EME YIELDS CHANGES
IN US SOVEREIGN YIELDS
‐1.5
‐1
‐0.5
0
0.5
1
1.5
2
2.5
3
China
Malaysia
Philippines
Indonesia
Hong Kong SAR
Poland
Czech Republic
Thailand
Turkey
Hungary
Korea
Brazil
Chile
Colombia
Mexico
Peru
Note: the squares indicate the average observed response (2-day change). The blue area
represents the average and the one-standard deviation of each country’s model response for
the multivariant panel-data model (table 11, specification 3).
BANCO DE ESPAÑA
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DOCUMENTO DE TRABAJO N.º 1606
FIGURE 4. MODEL RESPONSE TO AN INCREASE IN US SOVEREIGN YIELD AND US HIGH
YIELD SPREAD. DECEMBER 2014
-0.5
0
0.5
1
1.5
2
%
China
Malaysia
Philippines
Indonesia
1 pp change in US Sovereign bonds
1 pp change in US Sovereign and High yield bonds
Average change
Hong Kong SAR
Poland
Czech Republic
Thailand
Turkey
Hungary
Korea
Brazil
Chile
Colombia
Mexico
Peru
Note: Average response of countries to 100 bp increase in US sovereign yields (red bar) and 100 bp
increase in US sovereign yields and high-yield spread (blue bar). It uses the multivariate panel-data
model (table 11, specification 3).
BANCO DE ESPAÑA
36
DOCUMENTO DE TRABAJO N.º 1606
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GALO NUÑO and CARLOS THOMAS: Monetary policy and sovereign debt vulnerability.
1518
CRISTIANA BELU MANESCU and GALO NUÑO: Quantitative effects of the shale oil revolution.
1519
YAEL V. HOCHBERG, CARLOS J. SERRANO and ROSEMARIE H. ZIEDONIS: Patent collateral, investor commitment
and the market for venture lending.
1520
TRINO-MANUEL ÑÍGUEZ, IVAN PAYA, DAVID PEEL and JAVIER PEROTE: Higher-order risk preferences, constant
relative risk aversion and the optimal portfolio allocation.
1521
LILIANA ROJAS-SUÁREZ and JOSÉ MARÍA SERENA: Changes in funding patterns by Latin American banking systems:
how large? how risky?
1522
JUAN F. JIMENO: Long-lasting consequences of the European crisis.
1523
MAXIMO CAMACHO, DANILO LEIVA-LEON and GABRIEL PEREZ-QUIROS: Country shocks, monetary policy
expectations and ECB decisions. A dynamic non-linear approach.
1524
JOSÉ MARÍA SERENA GARRALDA and GARIMA VASISHTHA: What drives bank-intermediated trade finance?
1525
GABRIELE FIORENTINI, ALESSANDRO GALESI and ENRIQUE SENTANA: Fast ML estimation of dynamic bifactor
Evidence from cross-country analysis.
models: an application to European inflation.
1526
YUNUS AKSOY and HENRIQUE S. BASSO: Securitization and asset prices.
1527
MARÍA DOLORES GADEA, ANA GÓMEZ-LOSCOS and GABRIEL PEREZ-QUIROS: The Great Moderation in historical
perspective. Is it that great?
1528
YUNUS AKSOY, HENRIQUE S. BASSO, RON P. SMITH and TOBIAS GRASL: Demographic structure and
macroeconomic trends.
1529
JOSÉ MARÍA CASADO, CRISTINA FERNÁNDEZ and JUAN F. JIMENO: Worker flows in the European Union during
the Great Recession.
1530
CRISTINA FERNÁNDEZ and PILAR GARCÍA PEREA: The impact of the euro on euro area GDP per capita.
1531
IRMA ALONSO ÁLVAREZ: Institutional drivers of capital flows.
1532
PAUL EHLING, MICHAEL GALLMEYER, CHRISTIAN HEYERDAHL-LARSEN and PHILIPP ILLEDITSCH: Disagreement
about inflation and the yield curve.
1533
GALO NUÑO and BENJAMIN MOLL: Controlling a distribution of heterogeneous agents.
1534
TITO BOERI and JUAN F. JIMENO: The unbearable divergence of unemployment in Europe.
1535
OLYMPIA BOVER: Measuring expectations from household surveys: new results on subjective probabilities of future
house prices.
1536
CRISTINA FERNÁNDEZ, AITOR LACUESTA, JOSÉ MANUEL MONTERO and ALBERTO URTASUN: Heterogeneity
of markups at the firm level and changes during the great recession: the case of Spain.
1537
MIGUEL SARMIENTO and JORGE E. GALÁN: The influence of risk-taking on bank efficiency: evidence from Colombia.
1538
ISABEL ARGIMÓN, MICHEL DIETSCH and ÁNGEL ESTRADA: Prudential filters, portfolio composition and capital ratios
in European banks.
1539
MARIA M. CAMPOS, DOMENICO DEPALO, EVANGELIA PAPAPETROU, JAVIER J. PÉREZ and ROBERTO RAMOS:
Understanding the public sector pay gap.
1540
ÓSCAR ARCE, SAMUEL HURTADO and CARLOS THOMAS: Policy spillovers and synergies in a monetary union.
1601
CHRISTIAN CASTRO, ÁNGEL ESTRADA and JORGE MARTÍNEZ: The countercyclical capital buffer in Spain:
an analysis of key guiding indicators.
1602
TRINO-MANUEL ÑÍGUEZ and JAVIER PEROTE: Multivariate moments expansion density: application of the dynamic
equicorrelation model.
1603
ALBERTO FUERTES and JOSÉ MARÍA SERENA: How firms borrow in international bond markets: securities regulation
and market segmentation.
1604
ENRIQUE ALBEROLA, IVÁN KATARYNIUK, ÁNGEL MELGUIZO and RENÉ OROZCO: Fiscal policy and the cycle
in Latin America: the role of financing conditions and fiscal rules.
1605
ANA LAMO, ENRIQUE MORAL-BENITO and JAVIER J. PÉREZ: Does slack influence public and private labour
market interactions?
1606
FRUCTUOSO BORRALLO, IGNACIO HERNANDO and JAVIER VALLÉS: The effects of US unconventional monetary
policies in Latin America.
Unidad de Servicios Auxiliares
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